Power converters are complex circuits having both power and mixed signal processing. Such circuits also have a wide range of applications, and the continuous operation of these converters is imperative in most cases. In order to ensure a failure-free operation, converters employed in critical applications are being operated with redundancy and need to go through periodic maintenance and replacements. Generally, this periodic maintenance is implemented when the converter meets a calculated mean time to failure (MTTF). Accordingly, it is desirable to have power converters maintaining a failure-free operation until they reach the calculated MTTF. Such periodic maintenance is time and cost intensive which places a large burden on an entity when maintenance is required.
Unfortunately, the functionality and performance of a power converter degrades with time, and the amount of degradation may depend on several associated factors (i.e. more than just time) such as any overload, ambient temperature, switching impulses, loading variation and so on. Each of these stressful conditions may lead to severe degradation of the critical components in the converter or even can cause permanent damage in some cases. Over longer periods, these conditions coupled with various other environmental factors (mechanical vibration, high temperature, radiation) cause continuous aging of converter components which in turn cause gradual performance degradation.
Therefore, effectiveness and utilization factor of power converters could be greatly enhanced if the power converters' state of health could be identified with a reasonable degree of accuracy. To the knowledge of the inventors, there is no known technique to predict the remaining life or state of health of a power converter while the power converter is operational, and the accurate time to replace the power converter cannot be calculated using conventional prediction models.